Results for “cloud detector” — Page 7

NASA NTRS1979

Hydrogen chloride partitioning in a Titan III exhaust cloud diluted with ambient air

Measurements and analysis are presented of the partitioning of HCl between hydrochloric acid aerosol and gaseous HCl in a Titan III exhaust cloud, as the cloud is diluted with humid ambient air. Partitioning was determined by measuring the gaseous HCl concentration with a recently developed airborne Gas Filter Correlation detector and simultaneously with a chemiluminescence detector which measures total HCl. Although equilibrium predictions for HCl aerosol formation indicated that no HCl aerosol should exist in the exhaust cloud for the meteorological conditions of this launch, the measurements indicated significant HCl aerosol formation. These measurements will provide verification for advanced modeling programs now under development.

Sebacher, D. I.↗

NASA NTRS1975

Effluent sampling of Titan 3 C vehicle exhaust

Downwind in situ ground-level measurements of the exhaust from a Titan 3 C launch vehicle were made during a normal launch. The measurement activity was conducted as part of an overall program to obtain field data for comparison with the multilayer dispersion model currently being used to predict the behavior of rocket vehicle exhaust clouds. All measurements were confined to land, ranging from the launch pad to approximately 2 kilometers downwind from the pad. Measurement systems included detectors for hydrogen chloride (HCl), carbon dioxide (CO2), and particulates (Al2O3). Airborne and ground-based optical systems were employed to monitor exhaust cloud rise, growth, and movement. These measurement systems, located along the ground track (45 deg azimuth from the launch pad) of the exhaust cloud, showed no effluents attributable to the launch. Some hydrogen chloride and aluminum oxide were detected in the surface wind direction (15 deg azimuth) from the pad. Comparisons with the model were made in three areas: (1) assumption of cloud geometry at stabilization; (2) prediction of cloud stabilization altitude; and (3) prediction of the path of cloud travel. In addition, the importance of elemental analyses of the particulate samples is illustrated.

Gregory, G. L.↗

NASA NTRS2000

The Geoscience Laser Altimeter System (GLAS) for the ICESAT Mission

The Laser In space Technology Experiment, Shuttle Laser Altimeter and the Mars Observer Laser Altimeter have demonstrated accurate measurements of atmospheric backscatter and Surface heights from space. The recent MOLA measurements of the Mars surface have 40 cm vertical resolution and have reduced the global uncertainty in Mars topography from a few km to about 5 m. The Geoscience Laser Altimeter System (GLAS) is a next generation lidar for Earth orbit being developed as part of NASA's Icesat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS is being developed to fly on a small dedicated spacecraft in a polar orbit with a 590 630 km altitude at inclination of 94 degrees. GLAS is scheduled to launch in the summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will continuously measure the vertical distance from orbit to the Earth's surface with 1064 nm pulses from a ND:YAG laser at a 40 Hz rate. Each 5 nsec wide laser pulse is used to produce a single range measurement, and the laser spots have 66 m diameter and about 170 m center-center spacings. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a 1 m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when over sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid to about 8 urad is needed to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the orientation of the star camera and gyroscope permits the precise pointing angle of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring the vertical profile of laser energy backscattered by the atmosphere at both 1064 and 532 nm. The 1064 nm measurements use the Si APD detector and profile the height and vertical structure of thicker clouds. The measurements at 532 nm use new highly sensitive photon counting, detectors, and measure the height distributions of very thin Clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.

Abshire, James B.↗

DOE OSTI2023

CPC data from TAMU TRACER campaign in the Houston, TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow is directed through a cyclone impactor (Brechtel, Inc. Model SCC 0.732) and 0.3 LPM is directed to the CPC. To correct the data for particle losses, we used a two-step method. First, the measured SMPS size distributions were used to calculate total particle loss through the inlet for every SMPS scan at a single deployment location. Second, the CPC data was corrected for particle losses using the average of the total losses per scan. This calculation was done separately for each deployment location due to changes in the measured size distributions between locations. Particle loss from diffusion (based on Kesten, 1991 and Gormley, 1949), inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977), and cyclone impactor efficiency (based on Dirgo, 1985) were included in the loss calculation. When the SMPS was not sampling at a location (in the case of an instrument malfunction or operator error), the reported CPC data was corrected with an average of the total losses for the entire campaign at the specified deployment location (e.g., if we needed to correct Galveston data, then the average of all calculated losses at Galveston was taken). These flatline corrections were used for all data on 22/07/13, 22/07/20, 22/07/22, and the data from Galveston on 22/08/09. An additional flatline correction of 14% was applied to all CPC data based on laboratory calibration prior to and after the campaign. In laboratory calibrations, we identified that for the same sample of air the field CPC (GRIMM Model 5.403 CPC) undercounted the total concentration of particles by 14% compared to the ground truth laboratory CPC (TSI Model 3750). This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977. Dirgo et. al. Cyclone Collection Efficiency: Comparison of Experimental Results with Theoretical Predictions. Aerosol Science and Technology, 4:4, 401-415, 1985.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

CCN data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow is directed through a cyclone impactor (Brechtel, Inc. Model SCC 0.732) and 0.5 LPM is directed to the CCN. To calculate particle losses, we used a two-step method. First, the measured SMPS size distributions were used to calculate particle loss through the inlet during sampling. Second, the corrected SMPS data was used to calculate the average of the total losses per scan down the CCN line. Then, the correction was applied to the CCN data. This calculation was done separately for each deployment location due to changes in the measured size distributions between locations. Particle loss from diffusion (based on Kesten, 1991 and Gormley, 1949), inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977), and cyclone impactor efficiency (based on Dirgo, 1985) were included in the loss calculation. When the SMPS was not sampling at a location (in the case of an instrument malfunction or operator error), the reported CPC data was corrected with an average of the total losses for the entire campaign at the specified deployment location (e.g., if we needed to correct Galveston data, then the average of all calculated losses at Galveston was taken). These flatline corrections were used for all data on 22/07/13, 22/07/20, 22/07/22, and the data from Galveston on 22/08/09. The supersaturation uncertainty is estimated conservatively at +/- 0.03%, where variation in the inlet temperature, pressure, and calibration technique prevents a more accurate measurement. Confidence in the reported supersaturation measurements is based on a pre-campaign calibration (following the methods from our previous work and Deng, 2014 based on Rose, 2008) in addition to inter-comparisons with the DOE for two days (22/08/18 and 22/09/01) where TAMU was co-located with AMF1. The inter-comparisons show good agreement between our instrument and the DOEs instrument on both days at all supersaturations. After the last inter-comparison on 22/09/01, there was no indication of a malfunction by our instrument through the rest of the campaign. Unfortunately, the instrument was dropped during demobilization. A post-campaign calibration was conducted, which showed a substantial departure from the pre-campaign calibration. The drop may have damaged the instrument’s ability to produce the desired supersaturations. Therefore, we do consider the data after 22/09/01 to be correct, but it should be used with caution. The CCN counter sampled for 3 minutes at each supersaturation setpoint (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2%). At the end of a cycle, the instrument was set to 0.01% supersaturation for 5 minutes. The data is comprised of the last 60 seconds of each supersaturation set point (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2%) to ensure the instrument stabilized and was able to reach thermal equilibrium. We removed the data during the periods where there were operational difficulties, setup, or maintenance. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Rose et. al. Calibration and Measurement Uncertainties of a Continuous-Flow Cloud Condensation Nuclei Counter (DMT-CCNC): CCN Activation of Ammonium Sulfate and Sodium Chloride Aerosol Particles in Theory and Experiment. Atmos. Chem. Phys., 8, 1153-1179, 2008. Deng et. al. Using Raman Microspectroscopy to Determine Chemical Composition and Mixing State of Airborne Marine Aerosols over the Pacific Ocean. Aerosol Science and Technology, Vol 48, Issue 2, 2014. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977. Dirgo et. al. Cyclone Collection Efficiency: Comparison of Experimental Results with Theoretical Predictions. Aerosol Science and Technology, 4:4, 401-415, 1985.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SMPS data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow, 1.0 LPM, is directed through TSI's 0.071 cm impactor attached to the classifier of the SMPS setup. The SMPS’s DMA and CPC are connected through a 20.3 cm length of 0.48 cm diameter tubing. Measured SMPS size distributions were used to calculate size-dependent particle losses for each SMPS scan. Particle losses from diffusion (based on Kesten, 1991 and Gormley, 1949) and inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977) were included in the loss calculation. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Ice nucleation measurements from DRUM impactors during TRACER campaign in the Houston TX region from July to September 2022

During TRACER, three Davis Rotating Uniform size-cut Monitors (DRUM; DRUMAir 4-DRUM) were used to collect aerosols for ice nucleation measurements in the Brooks laboratory at Texas A&M University. The three instruments were located at AMF1 in La Porte, Ancillary site in Guy (ANC), and onboard the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V). ROAM-V was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and one of the Davis Rotating Uniform size-cut Monitors (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Each DRUM sampler was operated at a flow rate of 23 LPM. Each DRUM has four stages where the aerodynamic diameter size cuts are as follows: stage 1 larger than 3 μm, stage 2 from 3 to 1.2 μm, stage 3 from 1.2 to 0.34 μm, and stage 4 from 0.34 to 0.15 μm. Pretreated aluminum foil was used as a substrate on all stages. At AMF1 and ANC sites, the DRUMs were operated on the shared aerosol inlet, with generous support of the DOE ARM site staff. These instruments rotated 24 mm per day and only contained aluminum foil substrates. Substrates were changed weekly and transported to Texas A&M for storage in -80C freezer until analysis. The DRUM onboard ROAM-V was operated at a faster rotation rate of 150 mm per day to clearly separate the multiple deployment locations for ROAM-V. For the ROAM-V DRUM, substrates were changed every deployment and transported to Texas A&M for storage in -80C freezer until analysis. At Texas A&M, ice nucleation experiments were conducted to measure the ice nucleation temperature of the ambient aerosol samples collected from the three DRUMs using our previously established procedures (Alsante et al., 2023; Fornea et al., 2009; Matthews et al., 2023). For ice nucleation, only samples collected on stage 3 were analyzed, given that these are the most relevant size (1.2 to 0.34 μm diameter) for potential ice nucleating particles. For the AMF1 and ANC sites, we cut and analyzed 2 mm (2-hour) samples. We analyzed the time periods of the AMF1 site instrument when the ROAM-V was deployed. A 72-hour period from July 11th at 23:49 through July 15th at 1:49 was analyzed from the ANC site instrument. For the ROAM-V instrument, we separated the daily samples by site location. Between 1- and 6-hour independent samples were analyzed at each location. We also cut the ROAM-V samples in half to allow for compositional analysis of the aerosol on the other half of the substrate. All viable samples from the ROAM-V were analyzed. Analysis was done using a custom-built ice nucleation apparatus, recently updated to include an array of 16 individual samples (Matthews et al., 2023). On our experimental setup, we used 100 μL of Ultra-High-Performance Liquid Chromatography (UHPLC) water (Sigma Aldrich, >99.9% purity) to wash off the aerosol from the DRUM substrate. Then, we micropipetted 2 μL droplet samples into each of the 16 wells of the array, using hydrophobically coated microscope slides. Experiments would cycle 28 times from 10 C to -40C over a 20-hour period. During analysis of the TRACER samples, nine experiments were conducted with UHPLC water process blanks that followed an identical preparation procedure. The average freezing temperature and standard deviation for these process blanks is -27.7±2.4 C. This data was collected for ARM Field Campaign AFC07023 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Alsante, A. N., Thornton, D. C., & Brooks, S. D. (2023). Ice nucleation catalyzed by the photosynthesis enzyme RuBisCO and other abundant biomolecules. Communications Earth & Environment, 4(1), 51. Fornea, A. P., Brooks, S. D., Dooley, J. B., & Saha, A. (2009). Heterogeneous freezing of ice on atmospheric aerosols containing ash, soot, and soil. Journal of Geophysical Research: Atmospheres, 114(D13). DOI:10.1029/2009JD011958 Matthews, B. H., Alsante, A. N., & Brooks, S. D. (2023). Pollen Emissions of Subpollen Particles and Ice Nucleating Particles. ACS Earth and Space Chemistry.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Mini-Micropulse Lidar data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (mini-MPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. The mini-MPL deployed with ROAM-V is a 532 nm elastic and polarization lidar. The mini-MPL outputs normalized relative backscatter (NRB) derived from raw signal after after-pulse, overlap, and dead-time correction calibration. The depolarization ratio is calculated from the co-polarized and cross-polarized NRB (Flynna et al., 2007). The NRB and depolarization ratio data are resampled from the original data at 1-minute intervals. The vertical resolution of the mini-MPL data is 15 meters. The mini-MPL data can be used to determine the boundary layer, cloud top, and cloud bottom height and can be used to retrieve aerosol type and concentration profile. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu . Flynna, C. J., Mendozaa, A., Zhengb, Y., & Mathurb, S. (2007). Novel polarization-sensitive micropulse lidar measurement technique. Optics express, 15(6), 2785-2790.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Equivalent widths in spectropolarimetry can provide additional information on the atmosphere of Venus

It is demonstrated that the analysis in both intensity and polarization of equivalent widths of strong Venusian absorption lines can provide the most accurate location of the visible cloud top as well as the ratios of scale heights of CO2 to cloud particles and CO (or other appropriate minor constituent) to CO2. It is also shown that spectropolarimetric observations at different phase angles can provide a vertical sounding of the upper levels in the cloud. Equivalent widths in polarization are measurable on Venus with good infrared detectors, and their value is predicted to be approximately a few percent of those in intensity.

Buriez, J. C.↗

NASA NTRS2009

On the Quality of the Nimbus 7 LIMS Version 6 Water Vapor Profiles and Distributions

This report describes the quality of the Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) water vapor (H2O) profiles of 1978/79 that were processed with a Version 6 (V6) algorithm and archived in 2002. The V6 profiles incorporate a better knowledge of the instrument attitude for the LIMS measurements along its orbits, leading to improvements for its temperature profiles and for the registration of its water vapor radiances with pressure. As a result, the LIMS V6 zonal-mean distributions of H2O exhibit better hemispheric symmetry than was the case from the original Version 5 (V5) dataset that was archived in 1982. Estimates of the precision and accuracy of the V6 H2O profiles are developed and provided. Individual profiles have a precision of order 5% and an estimated accuracy of about 19% at 3 hPa, 14% at 10 hPa, and 26% at 50 hPa. Profile segments within about 2 km of the tropopause are often affected by emissions from clouds that appear in the finite field-of-view of the detector for the LIMS H2O channel. Zonally-averaged distributions of the LIMS V6 H2O are compared with those from the more recent Microwave Limb Sounder (MLS) satellite experiment for November, February, and May of 2004/2005. The patterns and values of their respective distributions are similar in many respects. Effects of a strengthened Brewer-Dobson circulation are indicated in the MLS distributions of the recent decade versus those of LIMS from 1978/79. A tropical tape recorder signal is present in the 7-month time series of LIMS V6 H2O with lowest values in February 1979, and the estimated, annually-averaged "entry-level" H2O is 3.5 to 3.8 ppmv. It is judged that this historic LIMS water vapor dataset is of good quality for studies of the near global-scale chemistry and transport for pressure levels from 3 hPa to about 70 to 100 hPa.

Remsberg, E. E.↗

DOE OSTI2022

Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles

The space-borne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006. To build long-term records from space-borne lidars useful for climate studies, one has to understand the differences between successive space lidars operating at different wavelengths, flying on different orbits, and using different viewing geometries, receiving paths, and detectors. In this article, we compare the results of Atmospheric Laser Doppler INstrument (ALADIN) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidars for the period from 28 June to 31 December 2019. First, we build a dataset of ALADIN–CALIOP collocated profiles (Δdist<1°; Δtime<6 h). Then we convert ALADIN's 355 nm particulate backscatter and extinction profiles into the scattering ratio vertical profiles SR(z) at 532 nm using molecular density profiles from Goddard Earth Observing System Data Assimilation System, version 5 (GEOS-5 DAS). And finally, we build the CALIOP and ALADIN globally gridded cloud fraction profiles CF(z) by applying the same cloud detection threshold to the SR(z) profiles of both lidars at the same spatial resolution. Before comparing the SR(z) and CF(z) profiles retrieved from the two analyzed lidar missions, we performed a numerical experiment to estimate the best achievable cloud detection agreement CDA norm (z) considering the differences between the instruments. We define CDA norm (z) in each latitude–altitude bin as the occurrence frequency of cloud layers detected by both lidars, divided by a cloud fraction value for the same latitude–altitude bin. We simulated the SR(z) and CF(z) profiles that would be observed by these two lidars if they were flying over the same atmosphere predicted by a global model. By analyzing these simulations, we show that the theoretical limit for CDA$_{norm}^{theor}$(z) for a combination of ALADIN and CALIOP instruments is equal to 0.81±0.07 at all altitudes. In other words, 19 % of the clouds cannot be detected simultaneously by two instruments due to said differences. The analyses of the actual observed CALIOP–ALADIN collocated dataset containing ~78 000 pairs of nighttime SR(z) profiles revealed the following points: (a) the values of SR(z) agree well up to ~3 km height. (b) The CF(z) profiles show agreement below ~3 km, where ~80 % of the clouds detected by CALIOP are detected by ALADIN as expected from the numerical experiment. (c) Above this height, the CDA$_{norm}^{obs}$(z) reduces to ~50 %. (d) On average, better sensitivity to lower clouds skews ALADIN's cloud peak height in pairs of ALADIN–CALIOP profiles by ~0.5±0.6 km downwards, but this effect does not alter the heights of polar stratospheric clouds and high tropical clouds thanks to their strong backscatter signals. (e) The temporal evolution of the observed CDA$_{norm}^{obs}$(z) does not reveal any statistically significant change during the considered period. This indicates that the instrument-related issues in ALADIN L0/L1 have been mitigated, at least down to the uncertainties of the following CDA$_{norm}^{obs}$(z) values: 68±12 %, 55±14 %, 34±14 %, 39±13 %, and 42±14 % estimated at 0.75, 2.25, 6.75, 8.75, and 10.25 km, respectively.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

The Cloud Detection and UV Monitoring Experiment (CLUE)

We propose a large-area, low-power instrument to perform CLoud detection and Ultraviolet monitoring, CLUE. CLUE will combine the W detection capabilities of the NIGHTGLOW payload, with an array of infrared sensors to perform cloud slicing measurements. Missions such as EUSO and OWL which seek to measure UHE cosmic-rays at 1W20 eV use the atmosphere as a fluorescence detector. CLUE will provide several important correlated measurements for these missions, including: monitoring the atmospheric W emissions &om 330 - 400 nm, determining the ambient cloud cover during those W measurements (with active LIDAR), measuring the optical depth of the clouds (with an array of narrow band-pass IR sensors), and correlating LIDAR and IR cloud cover measurements. This talk will describe the instrument as we envision it.

Barbier, L.↗

NASA NTRS2018

Imaging Technique for High Precision Measurement of Detector Stability for the Ocean Color Instrument

One of the new projects by NASA to explore environmental change is the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) spacecraft. The primary instrument aboard the PACE spacecraft is the Ocean Color Instrument (OCI), an advanced optical spectrometer that will measure the color of the ocean from the ultraviolet to shortwave infrared range for the purpose of observing and monitoring ocean and coastal biology. As part of the optical alignment testing that must be completed before the instrument is built, the measurement stability of the detectors at space flight operating temperatures must be determined to ensure alignment is maintained. Therefore, this project focuses on the development of an imaging technique that adheres to testing requirements and can be used to determine the stability of the OCI detector. The movements of targets affixed to a high-precision stage were analyzed through an image processing program to test the ability of the imaging technique to detect very small (under 10 micrometers) movements. It was found that movements as small as half a pixel (~6 microns) and 1 pixel (~12 microns) were able to be accurately and consistently detected with this imaging technique. This project found that the designed image analysis technique fulfills testing and measurement requirements and will be an effective metrology technique for the OCI detector stability test.

Optics↗

NASA NTRS2002

Micro-Pulse Lidar Signals: Uncertainty Analysis

Micro-pulse lidar (MPL) systems are small, autonomous, eye-safe lidars used for continuous observations of the vertical distribution of cloud and aerosol layers. Since the construction of the first MPL in 1993, procedures have been developed to correct for various instrument effects present in MPL signals. The primary instrument effects include afterpulse, laser-detector cross-talk, and overlap, poor near-range (less than 6 km) focusing. The accurate correction of both afterpulse and overlap effects are required to study both clouds and aerosols. Furthermore, the outgoing energy of the laser pulses and the statistical uncertainty of the MPL detector must also be correctly determined in order to assess the accuracy of MPL observations. The uncertainties associated with the afterpulse, overlap, pulse energy, detector noise, and all remaining quantities affecting measured MPL signals, are determined in this study. The uncertainties are propagated through the entire MPL correction process to give a net uncertainty on the final corrected MPL signal. The results show that in the near range, the overlap uncertainty dominates. At altitudes above the overlap region, the dominant source of uncertainty is caused by uncertainty in the pulse energy. However, if the laser energy is low, then during mid-day, high solar background levels can significantly reduce the signal-to-noise of the detector. In such a case, the statistical uncertainty of the detector count rate becomes dominant at altitudes above the overlap region.

Welton, Ellsworth J.↗

NASA NTRS2001

Geostationary Imaging FTS (GIFTS) Data Processing: Measurement Simulation and Compression

GIFTS (Geostationary Imaging Fourier Transform Spectrometer), a forerunner of next generation geostationary satellite weather observing systems, will be built to fly on the NASA EO-3 geostationary orbit mission in 2004 to demonstrate the use of large area detector arrays and readouts. Timely high spatial resolution images and quantitative soundings of clouds, water vapor, temperature, and pollutants of the atmosphere for weather prediction and air quality monitoring will be achieved. GIFTS is novel in terms of providing many scientific returns that traditionally can only be achieved by separate advanced imaging and sounding systems. GIFTS' ability to obtain half-hourly high vertical density wind over the full earth disk is revolutionary. However, these new technologies bring forth many challenges for data transmission, archiving, and geophysical data processing. In this paper, we will focus on the aspect of data volume and downlink issues by conducting a GIFTS data compression experiment. We will discuss the scenario of using principal component analysis as a foundation for atmospheric data retrieval and compression of uncalibrated and un-normalized interferograms. The effects of compression on the degradation of the signal and noise reduction in interferogram and spectral domains will be highlighted. A simulation system developed to model the GIFTS instrument measurements is described in detail.

Huang, Hung-Lung↗

NASA NTRS1999

Combined Satellite and Surface-Based Estimation of the Intracloud/ Cloud-to-Ground Lightning Ratio Over the Continental United States

Four years of observations from the NASA Optical Transient Detector (OTD) and Global Atmospherics National Lightning Detection Network (NLDN) are combined to determine the geographic distribution of the intracloud/cloud to ground lightning ratio over the continental United States. The mean ratio over this region is 2.64-2.94, with a standard deviation of 1.1-1.3 and anomalies as low as 1.0 or less over the Rocky and Appalachian mountains and as high as 8-10 in the central-upper midwest. There is some indication that the ratio covaries with ground elevation, although the relationship is nonunique. Little evidence is found to support a latitudinal covariance, despite significant variation in the climatological mean tropopause pressure over the latitudes considered. The dynamic range of local variability is comparable to the range of values cited by previous studies for latitudinal variation from the deep tropics to midlatitudes. Local high anomalies of this ratio in the midwest are coincident with anomalies in the climatological percentage of positive CG occurrence, as well as in the occurrence of large positive CGs characteristic of MCS convective and trailing stratiform regions. This suggests that storm type, morphology and level of organization may dominate over environmental cofactors in the local determination of this ratio.

Boccippio, D. J.↗

NASA NTRS1992

Multiple scattering lidar returns from stratus clouds

Multiple scattering lidar returns from stratus clouds were measured using a multi-field-of-view (MFOV) lidar operating at 1.054 microns. The detector consists of four concentric silicon photodiodes which define half-angle fields of view (FOV) of 3.8, 12.5, 25 and 38.5 mrad. The central FOV receives the conventional lidar signal, while the outer FOV's receive only multiply scattered contributions. The ratios of the signals in the outer FOV's to the signal in the central FOV is an indication of the lateral spreading of the scattered component of the laser pulse as it propagates through the cloud. MFOV lidar returns from stratus clouds measured between October 1991 and March 1992 can be divided into two distinct types, those with large multiple scattering ratios and those with small ratios. An example of each type of return is shown. Both measurements were made at an elevation angle of 45 degrees. Clouds with small multiple scattering signals probably have a high concentration of much larger particles on the order of hundreds of micrometers in size. This is a typical size range for suspended ice crystals or precipitations. Stratus clouds often have a high concentration of ice crystals even when there is no precipitation. Large ice crystals would give smaller signals in the outer FOV's because much of the scattered intensity is contained in a narrow diffraction peak with an angular width on the order of milliradians. The result is that for a given extinction, many more orders of scattering are required for the laser pulse to spread out. So far we have not been able to do simulations of MFOV lidar returns from ice crystal clouds because of uncertainties about the phase function of the crystals, particularly the magnitude of the backscatter peak at 180 degrees. On two occasions, MFOV lidar returns measured just prior to snowfall, showed a striking vertical profile. An example is shown. From 900 to 1300m, the multiply scattered signals are negligible compared to the return in the central FOV. Abruptly, at 1300m strong signals begin in the outer FOVs. These results could be explained by the presence of a cloud layer composed of water droplets at a range of 1300m (or 900m above ground) with snow precipitations forming at the bottom of the cloud. By measuring the polarization ratio of lidar signals, Pal and Carswell have observed snow precipitating from a cloud layer composed of water droplets. Based on these results, we believe that analysis of multiple scattering lidar returns can yield important information on the phase of cloud particles.

Hutt, D. L.↗

DOE OSTI2024

Constraints on directionality effect of nuclear recoils in a liquid argon time projection chamber

The direct search for dark matter in the form of weakly interacting massive particles (WIMP) is performed by detecting nuclear recoils produced in a target material from the WIMP elastic scattering. The experimental identification of the direction of the WIMP-induced nuclear recoils is a crucial asset in this field, as it enables unmistakable modulation signatures for dark matter. The Recoil Directionality (ReD) experiment was designed to probe for such directional sensitivity in argon dual-phase time projection chambers (TPC), that are widely considered for current and future direct dark matter searches. The TPC of ReD was irradiated with neutrons at the INFN Laboratori Nazionali del Sud. Data were taken with nuclear recoils of known directions and kinetic energy of 72 keV, which is within the range of interest for WIMP-induced signals in argon. The direction-dependent liquid argon charge recombination model by Cataudella et al. was adopted and a likelihood statistical analysis was performed, which gave no indications of significant dependence of the detector response to the recoil direction. The aspect ratio R of the initial ionization cloud is $R < 1.072$ with 90 % confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗